System and method for alkylation process analysis

ABSTRACT

A method and apparatus is provided for determining concentration of components in a liquid hydrocarbon mixture including hydrocarbons and water flowing through an alkylation process. A fluid flow path conveys the liquid continuously from the alkylation process through a first instrument configured for measuring a property of the liquid mixture, and having responsivities to concentration of the components, which are independent of the concentration of the water. A temperature detector generates temperature data for the liquid, and a second instrument measures another property of the liquid mixture. The instruments have mutually distinct responsivities to concentrations of the components. A processor captures data from the temperature detector and instruments, using the data with a model of responsivities of various concentrations of the components at various temperatures, to determine a temperature compensated concentration of the components while the liquid mixture flows continuously through the fluid flow path.

RELATED APPLICATION

This application is a Continuation of U.S. patent application Ser. No.12/720,533 entitled System and Method for Alkylation Process Analysis,filed on Mar. 9, 2010, now U.S. Pat. No. 7,972,863 which is aContinuation-In-Part of U.S. patent application Ser. No. 12/509,212entitled System and Method for Alkylation Process Analysis, filed onJul. 24, 2009, which claims the benefit of U.S. Provisional ApplicationSer. No. 61/084,142 entitled Multi-Property Measurement, filed on Jul.28, 2008, the contents of each of which are incorporated herein byreference in their entirety for all purposes.

BACKGROUND

1. Technical Field

This invention relates to chemical analysis, and more particularly toalkylation process analysis and control.

2. Background Information

Introduction to the Refining Alkylation Market

Between a quarter and a third of the world's refineries operatealkylation units, which convert relatively low-value byproducts of thecrude oil refining process into alkylate, a high octane component usedto make gasoline. Among the numerous control variables that determinethe economics of alkylation is the composition of the acid catalyst.Globally, the number of alkylation units using hydrofluoric acid (HF) iscurrently about 125 versus about 90 using sulfuric acid (H₂SO₄ or SA).Slightly more than half of all alkylation units in the world are locatedin North America, where gasoline is favored over diesel as a motor fuelfor passenger cars and alkylate is accordingly a valued blendingcomponent.

Another important application of alkylation technology is in theproduction of LABs (linear alkyl benzenes), important as a raw materialused in laundry detergents. However, the total number of alkylationunits in operation to produce LABs, as well as tonnage produced, israther small compared with the refining industry.

Background: Alkylation Process Control

Alkylate is one of the most important gasoline blending components inthe refining industry. Because it has an extremely high octane number,contains virtually no sulfur, and can be produced using olefinicby-products from the fluidized catalytic cracking (FCC) unit, alkylatehas been called refiners' gold. Given that the reactants are seldompure, and that propylene is sometimes mixed with the olefin feed,alkylate in practice comprises a mixture of compounds instead of pureisooctane as depicted in the following idealized equation:Isobutane+Isobutene→3,3,5-trimethypentane(Isooctane)

Produced in a continuous-flow process, the chemical addition ofisobutane and isobutene is effected conventionally through liquid phasecatalysis involving strong acids such as hydrofluoric acid (HF) andsulfuric Acid (H₂SO₄, or SA), although solid phase catalysts arecurrently under development.

Monitoring and controlling the composition of the liquid acid catalyst,i.e., acid strength and the levels of impurities that dilute the acid,are among the most important challenges associated with the profitableoperation of the alkylation process. One important impurity is water,which enters the process with the feed streams. Though present at ppm(parts per million) levels, water accumulates in acid catalyst atpercent levels due to feed rates ranging from a few thousand barrels perday (bpd) to tens of thousands of bpd. By contrast, acid soluble oil(ASO, as defined hereinbelow) accumulates in the acid catalyst, aby-product of reactions involving feed impurities that contain sulfur,oxygen, or conjugated double bonds.

HF Alkylation

In the case of HF alkylation (HFA), water generally is controlled atlevels below 2% to minimize corrosion of equipment in the unit. Also,total hydrocarbons dissolved in the catalyst are typically held atlevels around 11%-16% to yield alkylate of the required quality andmaximize process economics. In HFA, HF strength is controlled throughacid regeneration within the alkylation unit, which is essentially adistillation process that separates HF from the higher-boilingimpurities, H₂O and ASO (Acid Soluble Oil, as defined hereinbelow).

If HF strength drops below about 80%, side reactions can accelerate andlead to a condition called acid runaway, which consumes HF and produceslarge amounts of ASO. Such runaways rarely occur, as unit operatorsusually have time to detect the incipient runaway and “pull charge”(withhold olefin feed) to stop the process before the runaway conditionactually occurs. However, this action also stops the production ofalkylate while the catalyst is regenerated. Furthermore, acidregeneration itself has associated costs including energy required torun the unit, neutralization and disposal of hydrocarbon byproducts, andthe addition of fresh, pure HF. Thus, the ability to monitor and controlcatalyst composition in real time allows refiners to avert runaways,reducing operating costs while also tending to maximize product quality(octane), throughput, and the time between maintenance shutdowns torepair or replace corroded components.

SA Alkylation

SA alkylation (SAA) differs from HFA in that the catalyst generally isnot, with rare exception, regenerated on site at the refinery. HF has arelatively low boiling point and can be distilled. By contrast, SA isessentially non-volatile and therefore cannot be purified throughdistillation. Rather the “spent” acid generally must be shipped by railcar for remote processing. Thus, the high cost associated with off-siteregeneration partially offsets the perceived safety advantage of SA overHF, i.e., its low volatility.

Given that the alkylation reaction occurs only when acid strength issufficiently high to catalyze the reaction of isobutane with olefins,the effectiveness of SA diminishes when its strength falls below acertain level due to accumulation of ASO and H₂O—typically around88%-90%. Thus, the economics of SA alkylation depend on knowing exactlythe point where SA becomes too weak and must be taken out of service.For example, taking SA out of service when its strength is 89% may bevery costly if good quality alkylate can be produced economically withacid strength≧88.5%.

Traditional Analysis of Acid Catalyst

The composition of acid catalyst is typically determined by manuallyobtaining a sample for analysis in the local refinery laboratory daily,weekly, or several times each week. In contrast with hydrocarbon samplesroutinely analyzed in the refinery lab, full analysis of acid catalystsamples tends not to be straightforward due to special requirements forsample handling, preparation, and analysis. Additionally, HF presents asafety hazard due to its volatility and toxicity. With both HF and SA,comprehensive determination of composition is difficult for at least tworeasons. First, measurement of water generally depends on a Karl Fischertitration method specially modified to neutralize the strong acid.Second, ASO is not a single compound, but includes a range ofchemically-related compounds that have a rather wide range of molecularweights and boiling points, some of which (e.g., “light ASO”) canevaporate rapidly at room temperature.

Analysis Frequency

In consideration of the foregoing difficulties, refiners may test theacid as infrequently as possible to minimize laboratory workload. Somerefiners make do with one analysis per week while refineries operatingin Los Angeles County, Calif. may be required by regulation to test HFcatalyst once every 8 hours. Infrequent analysis may be sufficient topermit process control under stable operating conditions, but not toidentify rapid changes caused by occasional surges in feed impuritiesthat lead to generation of ASO.

Analytical Reproducibility and Completeness

Compounding the issue of analysis frequency, laboratory test results maynot always be reliable due to the difficulty of obtaining arepresentative sample when sample volumes are minimized in considerationof safety, as may be done in the case of HF catalyst. This furthercompounds the difficulty of reproducibly executing the test methoditself. And if technicians running the tests do not routinely performthe Karl Fischer water measurement, acid strength measured by titrationmay be the only parameter known in regard to catalyst composition,severely limiting operators' ability to optimize the process.

Safety

As mentioned, HF is both volatile and toxic. Sampling, sample handling,and testing therefore are executed in accordance with audited procedurescarefully designed to ensure the safety of operators and technicians. Inthe case of HF, testing frequency may be deliberately suppressed tominimize exposure risks.

All of this underscores the undesirability of manual methods for routineanalysis. Attempts have been made to replace manual sampling and testingwith online measurement techniques, to facilitate the efficient and safeoperation of alkylation units. To date, however, these attempts havegenerally been unsatisfactory, e.g., due to incomplete or inaccuratemeasurements by simple univariate instruments; or due to excessivecomplexity, lower-than-desired reliability and/or relatively high costs,such as associated with conventional use of spectrometric technologies.Thus, a need exists for an improved analyzer system for real-timealkylation process analysis and control.

SUMMARY

According to one aspect of the invention, an apparatus is provided foron-line concentration determination of components in a liquidhydrocarbon mixture flowing through an alkylation process, which liquidhydrocarbon mixture includes an unknown concentration of componentsincluding hydrocarbons and water. The apparatus includes a fluid flowpath configured to convey the liquid mixture continuously in adownstream direction from the alkylation process. An instrument islocated along the fluid flow path and is configured for measuring aproperty of the liquid mixture, the instrument having responsivities toconcentrations of one of the components, substantially independent ofthe concentrations of the water. A temperature detector is configured togenerate temperature data for the liquid mixture, and a secondinstrument located along the fluid flow path is configured for measuringanother property of the liquid mixture. The first and second instrumentsare configured to have mutually distinct responsivities toconcentrations of the components. A processor is configured to capturedata generated by the temperature detector and the first and secondinstruments, and to use the data in combination with a model ofresponsivities to various concentrations of the components at varioustemperatures, to determine a temperature compensated concentration ofthe components in the liquid mixture while the liquid mixture flowscontinuously through the fluid flow path.

In another aspect of the invention, an apparatus is provided for on-linedetermination of levels of at least three properties in a liquid mixturewhich contains unknown levels of the properties. The apparatus includesa fluid flow path configured to convey the liquid mixture continuouslyin a downstream direction therethrough, and a Raman spectrometer locatedalong the fluid flow path, and configured for measuring a first propertyof the liquid mixture. A separator is located upstream of the Ramanspectrometer along the fluid flow path, to remove hydrocarbon present ina gas or liquid phase distinct from that of the liquid mixture, so thatthe liquid mixture is conveyed continuously through the Ramanspectrometer. The Raman spectrometer is configured to haveresponsivities to concentration of one of the components, substantiallyindependent of the concentrations of the water. A conductivity sensor islocated along the fluid flow path, and configured for measuringconductivity of the liquid mixture. The Raman spectrometer and theconductivity sensor are configured to have mutually distinctresponsivities to levels of the components. A processor is configuredfor capturing data generated by the Raman spectrometer and conductivitysensor and using the data in combination with a model of responsivitiesto various levels of the properties at various temperatures, todetermine levels of the properties in the liquid mixture while theliquid mixture flows continuously through the fluid flow path.

In yet another aspect of the invention, a method is provided for on-lineconcentration determination of components in a liquid hydrocarbonmixture flowing through an alkylation process, which liquid hydrocarbonmixture includes an unknown concentration of components includinghydrocarbons and water. The method includes supplying the liquid mixturein a downstream direction along a fluid flow path to a first instrumentconfigured to have responsivities to concentrations of one or more ofthe components substantially independent of the concentrations of thewater. The acid catalyst is supplied to a temperature detector and to asecond instrument configured to have responsivities to concentrations ofwater, wherein the first and second instruments are configured to havemutually distinct responsivities to concentrations of the components.Properties of the liquid mixture are measured using the first and secondinstruments. A processor captures data generated by the first and secondinstruments and the temperature detector, and uses the data incombination with a model of responsivities to various concentrations ofthe components at various temperatures, to generate a temperaturecompensated concentration of the components in the liquid mixture, whilethe liquid mixture flows continuously through the fluid flow path.

In still another aspect of the invention, a method is provided foron-line concentration determination of the composition of a liquidmixture which contains unknown levels of at least three components. Themethod includes supplying the liquid mixture to at least first andsecond instruments having mutually distinct responsivities to levels ofthe three components, at least one of the instruments being a Ramanspectrometer and the other being a conductivity sensor. The liquidmixture is supplied to the Raman spectrometer through a separator toremove hydrocarbon present in a gas or liquid phase distinct from thatof the liquid mixture, so that the liquid mixture is conveyedcontinuously through the Raman spectrometer. First and second propertiesof the liquid mixture are measured using the first and secondinstruments respectively. Data generated by the first and secondinstruments is captured and used in combination with a model ofresponsivities to various levels of the components at varioustemperatures, to determine levels of the at least three components inthe liquid mixture.

The features and advantages described herein are not all-inclusive and,in particular, many additional features and advantages will be apparentto one of ordinary skill in the art in view of the drawings,specification, and claims. Moreover, it should be noted that thelanguage used in the specification has been principally selected forreadability and instructional purposes, and not to limit the scope ofthe inventive subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a plot of an NIR spectrum of HF Alkylation Catalyst;

FIG. 2 is a plot of an NMR spectrum of Sulfuric Acid AlkylationCatalyst;

FIG. 3 is a plot of component concentrations in HF catalyst versus time;

FIG. 4 is a plot of percent hydrocarbon versus percent HF in alkylationcatalyst;

FIG. 5 is a schematic diagram of an embodiment of an acid catalystanalyzer of the present invention, with optional portions shown inphantom;

FIGS. 6 and 7 are views similar to that of FIG. 5, of optionalembodiments of acid catalyst analyzers of the present invention;

FIG. 8 is a flow diagram showing calibration of embodiments of thepresent invention; and

FIG. 9 is a flow diagram showing validation of property measurementsgenerated by embodiments of the present invention.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings that form a part hereof, and in which is shown byway of illustration, specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention, and it is tobe understood that other embodiments may be utilized. It is also to beunderstood that structural, procedural and system changes may be madewithout departing from the spirit and scope of the present invention. Inaddition, well-known structures, circuits and techniques have not beenshown in detail in order not to obscure the understanding of thisdescription. The following detailed description is, therefore, not to betaken in a limiting sense, and the scope of the present invention isdefined by the appended claims and their equivalents. For clarity ofexposition, like features shown in the accompanying drawings areindicated with like reference numerals and similar features as shown inalternate embodiments in the drawings are indicated with similarreference numerals.

GENERAL OVERVIEW

This disclosure describes a system and method for (e.g., online)composition measurement of acid catalyst used in alkylation units of thetype currently operating in roughly 30% of the world's oil refineries.Compared with available spectrometric technologies, embodiments of thepresent invention substantially satisfy requirements for broad adoptionby refiners globally: ease of implementation, analytical reliability(accuracy), operational reliability (low maintenance), andcost-effectiveness. Particular embodiments do so by combining two ormore relatively low-cost sensor devices that tend to be both simple andinexpensive compared with conventional spectrometers. As will bediscussed in greater detail hereinbelow, examples of such relativelylow-cost sensor devices include, but are not limited to, the Foxboro871FT toroidal conductivity sensor and the CFS10 Coriolis flowmeter,both available from Invensys Systems, Inc. (Foxboro, Mass., USA). Otherembodiments enable the use of spectrometers without the need forrelatively complex and expensive isothermal sample conditioning.

Where used in this disclosure, the term “property” refers to chemicaland/or physical characteristics of a material, independently of itsrelative concentration within a mixture. The terms “computer” and“processor” are meant to encompass a workstation, personal computer,personal digital assistant (PDA), wireless telephone, or any othersuitable computing device including a microprocessor, a computerreadable medium upon which computer readable program code (includinginstructions and/or data) may be disposed, and a user interface. Theterms “data system” and “model” are intended to refer to acomputer-related component, including hardware, software, and/orsoftware in execution. For example, a model may be, but is not limitedto being, a process running on a processor, a processor including anobject, an executable, a thread of execution, a mathematical equation orset of equations, a program, and a computer. Moreover, the variouscomponents may be localized on one computer and/or distributed betweentwo or more computers. The terms “real-time” and “on-demand” refer tosensing and responding to external events nearly simultaneously (e.g.,within milliseconds or microseconds) with their occurrence, or withoutintentional delay, given the processing limitations of the system andthe time required to accurately respond to the inputs. As used herein,the term “acid catalyst” refers to a liquid mixture (e.g., single phase)including an acid (HF or SA), water, and dissolved hydrocarbon (ASO). Itis noted that the “acid strength” of the acid catalyst is commonlydefined as the concentration of the acid, and while the acid canfunction as a catalyst on its own, as a practical matter, and as usedherein, acid catalyst is understood to comprise the ternary mixture. Asused herein, the term “ASO” or “acid-soluble oil” refers tosubstantially any hydrocarbon that has been dissolved within an acid,alone or in combination with additional hydrocarbon that may have beenemulsified or otherwise mixed with acid in a liquid sample or on-lineprocess. For example, the term ASO (or “polymer”) refers primarily tohydrocarbon that has been dissolved, emulsified or otherwise mixed withHF or SA to form to form a nominally single-phase mixture that persistsas such during online sampling and analysis. By contrast, the acidcatalyst sample may contain entrained light hydrocarbon, believed to besubstantially isobutane, in the form of phase-separated liquid or gas(IB/ps), either of which can be readily removed from the bulk acidcatalyst by means of a device of suitable design (e.g., a separator).

Referring now to FIGS. 1-9, embodiments of the present invention will bemore thoroughly described.

Criteria for an Online Analysis Solution

To overcome the issues of manual sampling and testing, the instantinventor(s) has sought an online analytical methodology which isrelatively straightforward to implement, reliable (mechanically robustwith respect to acid), sufficiently accurate to support processoptimization objectives, simple in overall design and operation, andcost-effective.

Additionally, installation of an online analyzer should not simplyexchange one set of risks for another. For example, maintenancetechnicians who previously had no exposure to HF may be required toservice an HF analyzer. Thus, solving the analytical problem should alsoenhance safety and reduce the overall risk of operator exposure.

A Question of Information Channels

Technologies that may be used with the embodiments disclosed hereingenerally fall into either of two classes: single-channel measurementinstruments; and multi-channel spectrometers. The following Table 1provides a representative comparison.

TABLE 1 Comparison of Technologies Applied for analysis of AlkylationCatalyst. INSTRUMENTS SPECTROMETERS DESCRIPTION Devices employingtechnology that Devices that measure a spectrum, responds directly andwhich in the general sense is a plot proportionately to variation in aof response (intensity) across a specific physical or chemical number ofchannels normally defined property in the sample, or measures in termsof frequency (or the response of such a property to a wavelength). Theresponse is a stimulus that it applies to a sample. measure of theinteraction of electromagnetic energy applied to the sample by thespectrometer at specific frequencies, or of the emission of energy bythe sample in response to the application of electromagnetic energy.CHARACTERISTICS On the whole, instruments are Complex compared withinstruments, simple, compact, have relatively low costing 20-50 times asmuch as cost, and generally require no instruments and usually requiringsample conditioning, but analyze a sample conditioning, e.g. to removestream as presented. Instruments phase-separated water or generally areunivariate devices that particulates or to provide tight supply a singlechannel of temperature control. Examples: NIR information in response toa specific (near infra-red) and NMR (nuclear chemical or physicalchange, but are magnetic resonance) spectroscopy. not suitable formeasuring an effect By definition, spectrometers are that has two ormore causes. multi-channel, multi-variable analyzers. CALIBRATION,Generally, the calibration is a simple Calibration normally relies onmulti- MATHEMATICS mathematical function applied to the variablechemometrics to build instrument's output in response to a propertymodels that are applied to physical or chemical property of the spectraof unknown samples for interest. Sometimes it is as simple propertyprediction. As a secondary as standardizing on two materials to or“referenced” methodology, define zero and span. The modeling requires asignificant instrument stability is generally population of samples onwhich lab stable enough to permit this tests have been performed, andfor calibration equation to be used for a which spectra have beenmeasured. long period of time. EXAMPLES pH probes and ion-selective NIR,FTNIR (Fourier Transform NIR), electrodes; viscometers; refractiveRaman, and NMR spectrometry index probes; beta gauges; densitometers;conductivity meters; simple photometers; flow meters; various water cutmeasurement technologies; temperature probes (RTDs, TCs, thermisters,PRTs, etc.) APPLIED TO THE Refractive Index FTNIR (for HF) ANALYSIS OFACID Densitometry Process NMR (for H₂SO₄) CATALYST ConductivityLIMITATION Univariate data High cost; sampling system (too littleinformation: complexity (to control temperature); one equation but threeunknowns) installation complexity (fiber optics for NIR)

Individual instruments referenced above are relatively simple, low cost,easy to implement, and functionally reliable but have heretoforegenerally been incapable of providing all the desired information at thedesired analytical accuracy. Spectrometers are relatively high cost,complex, more difficult to implement and maintain than instruments, buthave generally been able to provide the desired information.

As such, both classes of technology, as conventionally used, tend tooffer poor value in applications such as alkylation catalystanalysis—instruments because they are inexpensive but do not offercomprehensive analysis; spectrometers because of the disproportionateexpense to install and maintain, particularly their need for relativelycomplex sample conditioning systems capable of maintaining acid catalystsamples at a constant temperature. A desired analyzer for acid catalystshould approach or achieve the analytical performance of spectrometersand the comparatively low cost and simplicity of instruments. The aboveinventory of available instruments and analyzers therefore suggests adilemma. But the instant inventor(s) has discovered that the dilemma isa false one, the consequence of focusing on the analyzer rather than onthe information required.

Analytical Problem

Rather than search for a single analyzer that will perform the requiredmulti-component analysis, the instant inventor(s) has identified thetype of information needed to analyze acid catalyst online. This line ofthinking led first to the observation that three channels of differentor independent information are required. To understand this, considerthe case of a univariate instrument whose measured response R₁ varies asa function of changing concentration of acid (A), hydrocarbon (H), andwater (W). In a chemical system containing these three components withpercent concentrations A, H, and W, an equation for R₁ can be written asfollows:R ₁ =a ₁ ·A+h ₁ ·H+w ₁ ·W  (1)where a₁, h₁, and w₁ are the responsivities of the correspondingcomponents in the mixture for the particular instrument. It is axiomaticthat a single equation with three unknowns cannot be solved. This factexplains in mathematical terms why univariate instruments that measuredensity, refractive index, or conductivity have proven inadequate.

The inventor(s) understood that what is needed to solve for A, H, and Wis a system of three equations. One might conclude initially that twoadditional instruments would be required to provide responses requiredfor two additional equations:R ₂ =a ₂ ·A+h ₂ ·H+w ₂ ·W  (2)R ₃ =a ₃ ·A+h ₃ ·H+w ₃ ·W  (3)

However, the instant inventor(s) has recognized that the composition ofacid catalyst is mathematically bounded because the concentrations ofthree components sum to 100%. This means that the chemical system onlyhas two degrees of freedom, suggesting that its composition can bedetermined through addition of only one more instrument with a responseR₂:R ₁ =a ₁ ·A+h ₁ ·H+w ₁ ·WR ₂ =a ₂ ·A+h ₂ ·H+w ₂ ·W100=A+H+W  (4)

If A, H, and W are known for a set of calibration samples, and if theinstrument responses R₁ and R₂ are recorded for those samples, then theconstants a_(i), h_(i), and w _(i) can be determined. Subsequently,Equations (4) can be solved for A, H, and W by measuring R₁ and R₂ foran unknown sample.

Characteristics of the Analytical Solution

Equation (4) provides for the substantially complete determination ofalkylation catalyst composition with a 2-channel analyzer provided twoconditions are met. First, the responsivities a_(i), h_(i), and w _(i)for A, H, and W, respectively, should be sufficiently different so thatthe solution to the Equation (4) is robust across the applicable rangeof concentrations for A, H, and W. Second, variation in the responses R₁and R₂ depend substantially on variation in A, H, and W. If they do not,the implication would be that there is another degree of freedom causedby some chemical or physical effect, e.g., interactions between thecomponents or temperature variation. However, as taught in the aboveanalysis of the Analytical Problem, it has been found that thissituation may be addressed by the addition of another instrument whoseresponse uniquely relates to R₁, R₂, and the chemical or physicaleffect.

The nature of the measurement solution comes into clearer focus if waterand dissolved hydrocarbons, including ASO, are viewed as solutes and HFor SA as a solvent. When changes in water concentration are relativelysmall, then, referring to Eq. (1), the term w₁·W is relatively constant,in which case the chemical system has essentially a single one degree offreedom and Eq. (1) simplifies to R₁=h₁·H+C. Rearranging to express H interms of R₁ allows H to be measured straightforwardly as a function ofdensity; viscosity; capacitance (a function of a material's dielectricconstant); refractive index; absorption of electromagnetic radiation,e.g., microwave, infrared, near-infrared; and/or the emission of radiosignals by the sample in a low magnetic field (low-field NMR). However,in practice the term w₁·W in Equation (1) is non-zero and variable inmagnitude, explaining why univariate measurement devices used alone haveproven incapable of providing full characterization of alkylationcatalysts.

Similarly, if the hydrocarbon fraction is constant, a device selectivetoward water in acid may have a response function across theconcentration range relevant to acid catalysts. For example, referringto Equation (2), the Foxboro 871FT toroidal conductivity sensor is usedroutinely to measure low levels of water in HF with no dissolvedhydrocarbons present, i.e., H=0 and the term a₂·A is relativelyconstant. But in three-component acid catalyst systems the magnitude ofthe term h₂·H is nonzero and both A and H are variable, with theconsequence again that a single-channel instrument does not have asingular response.

Two Degrees of Freedom: Spectral Confirmation

The NIR (Near Infrared) spectrum of HF catalyst (FIG. 1) and NMR(Nuclear Magnetic Resonance) spectrum of SA catalyst (FIG. 2) confirmthe overall simplicity of the catalyst systems. As shown in FIG. 1, theNIR spectrum reveals three regions where the expressions of HF,hydrocarbon, and water are distinct if not fully resolved. While thismakes direct measurement of intensities difficult, common data treatmentand modeling techniques e.g., first derivatives and PLS (Partial LeastSquares regression), respectively, permit direct correlation betweenspectral intensities and concentration. As shown in FIG. 2, the NMRanalysis is actually less straightforward, as the spectrum shows onlytwo major sets of peaks because water in SA does not exist as freewater, but as a complex with SA. Therefore its concentration in the SAfraction is determined as a function of its effect on the position ofthe SA peak.

FIG. 3 shows that HF acid catalyst is a three-component system with twodegrees of freedom: the amount of water is low and relatively constantwhile the concentrations of HF and ASO vary as near-perfect mirrorimages. FIG. 4 further emphasizes that for HF catalyst, theconcentrations of acid and ASO relate in a nearly perfect linearfashion.

Hardware: Instruments and Sampling

Turning now to FIG. 5, an embodiment of the present invention, referredto as an Acid Catalyst Analyzer, or ACA, 20, includes a temperaturedetector 22, an instrument 24, and optionally, one or more otherinstruments 26, disposed along a fluid flow path 28 as shown. ACA 20also includes a (e.g., remote) data system (processor) 30 configured tocapture and process signals from the temperature detector 22 andinstruments 24, 26, etc., apply a model that interprets those signals,and the concentration of the catalyst, e.g., to a conventionalalkylation unit control system (not shown).

It should recognized that in some embodiments, an ACA 20 having only asingle instrument 24 may be used (e.g., in addition to temperaturedetector 22), such as for determining the on-line concentration of asingle component in the alkylation catalyst mixture flowing through analkylation process containing, i.e., an acid-soluble-oil (ASO), water,and HF or SA. In such a single-instrument embodiment, instrument 24 isconfigured to measure a property of the liquid mixture (e.g., acidcatalyst) as it flows through fluid flow path 28. It is noted that theresponse of the particular instrument to concentration changes in one ofthe three constituents of the liquid mixture is substantiallyindependent of the concentrations of the other constituents. In aparticular exemplary embodiment, for example, instrument 24 may includea conductivity detector such as the aforementioned Foxboro 871FTconductivity detector. As discussed herein, it is recognized thatconductivity is a response that is related to the concentration of waterin the liquid mixture, and is substantially independent of theconcentration of acid and ASO.

It should be recognized that instrument 24 may include any one ofvarious other types, such as may be responsive to concentrations ofeither the acid (HF or SA), the acid-water fraction, or ASO. Forexample, instrument 24 may be a photometric sensor or photometer,including the above-referenced NIR, FTNIR (Fourier Transform NIR),Raman, and/or NMR spectrometers, and/or water-cut meters (e.g., the RedEye® 2G Water-Cut Meter by Weatherford International, Ltd., Houston,Tex.). As still another option, instrument 24 may be a densitymeasurement device, such as a Coriolis flowmeter (e.g., Foxboro CFS10Coriolis flowmeter), which is responsive to changes in acid catalystdensity caused by changes in hydrocarbon content. Use of such a densitymeasurement device in a single-instrument embodiment has been shown toprovide substantially accurate results for HF and/or SA in acidcatalysts in the event the concentration of phase separated isobutane,IB/ps (liquid or gas) remains relatively constant over time. In theevent the IB/ps tends to vary significantly, then a separator may bedesired, as discussed with respect to the optional variation below.

The data generated by the single instrument 24 (e.g., conductivitydetector or other single channel device) and temperature detector (e.g.,Resistive Temperature Detector (RTD)) 22 may then be used in combinationwith a model, by processor 30 to determine a temperature compensatedconcentration of the particular constituent of interest (which in thisexample is water). (It should be noted that while the temperaturedetector is shown and described as a device configured to explicitlydetermine temperature (e.g., an RTD, thermocouple (TC), thermister,platinum resistance thermometer (PRT), or the like), temperaturedetector 22 may also include a device or data channel configured toenable implicit capture of temperature information, as will be discussedin greater detail hereinbelow.) Although not required, in particularembodiments, the output generated by processor 30 may be filtered (byoptional filter 25) in a manner that would be familiar to those skilledin the art in light of the instant disclosure, such as to provide asmoother output plot of concentration over time, e.g., when IB/ps ispresent at levels that may cause instantaneous, random variation, givingthe appearance of noise in a measured property of acid catalyst.

As mentioned above, in variations of the foregoing embodiments, it maybe desirable to provide a second instrument. This second (optional)instrument 26 is configured to measure another property of the liquidmixture, so that the instruments 24 and 26 have mutually distinctresponsivities to concentrations of the acid catalyst, ASO, and water.Processor 30 may then capture the data generated by the temperaturedetector 22 and both instruments 24, 26, and use the data in combinationwith the model to generate a temperature compensated concentration ofthe acid, the ASO, and water, in the liquid mixture. In particularembodiments, instrument 24 is a conductivity sensor and instrument 26measures density.

As a further option, the foregoing embodiments may be provided with aseparator 32 configured to remove hydrocarbon (e.g., IB/ps) present in agas or liquid phase distinct from that of the liquid mixture (acidcatalyst) sample stream, which otherwise behaves as a single phase. Asshown, separator 32 may be disposed at or upstream of at least one orboth of the instruments 24, 26, within fluid flow path 28. In particularembodiments, separator 32 is configured for continuous operation in aconventional manner, e.g., by passing liquid through to the fluid flowpath 28, while returning lighter, phase-separated material through asuitable return line, such as shown in FIG. 6. Use of such a separatorprovides a continuous flow of liquid sample to the instrument(s) andtemperature detector, to permit them to operate substantiallycontinuously, i.e., without having to stop the flow of fluid prior todata capture. Alternatively, as will be discussed below with respect toFIG. 7, a separator may be incorporated into one or more of theinstruments 24, 26, etc.

As a still further option, the various embodiments disclosed herein maybe provided with a heater 33, such as a conventional inline heatexchanger shown schematically in FIG. 5. In particular embodiments,heater 33 may be used simply to help ensure that the liquid mixtureentering the ACA from the process at 38 is maintained at or above apredetermined minimum temperature. For example, heater 33 may beparticularly useful when the ACA is operated in winter conditions, suchas to maintain the liquid mixture at a minimum level predetermined tohelp prevent dissolution (phase separation) of the liquid mixture duringflow through fluid flow path 28. As also shown, it may be desirable toplace heater 33 downstream of separator 32, so that IB/ps is removedprior to the application of heat. Heater 33 may also be useful tomaintain sample in a temperature range where the response of instrument24 or 26 to the change in a component concentration provides therequired measurement resolution. For example, at water levels relevantto SA alkylation, the change in conductivity, C, as a function of thechange of water concentration, W, i.e., dC/dW, is known to increase withtemperature. Therefore, a heater 33 incorporated into ACA 20 may be usedto heat the acid catalyst sample to a temperature sufficient to provideimproved sensitivity to the changing concentration of water in SAwithout vaporizing light hydrocarbons present in the mixture, e.g.,about 40° C. at typical process pressure.

In addition, although heater 33 may be conveniently disposed in linewith fluid flow path 28 as shown, substantially any type of heatercapable of maintaining the liquid mixture at or above the desiredpredetermined temperature may be used. For example, in the event thevarious components of the ACA are disposed within an optional cabinet52, such as shown in phantom, heater 33 may be a conventional spaceheater configured to maintain the interior of the cabinet 52 at or abovethe desired minimum temperature.

It should be recognized that although heater 33 may be used to maintainthe liquid mixture within flow path 28 within a predeterminedtemperature range, or above some minimum temperature, this is notrequired by the embodiments disclosed herein. Rather, as mentionedabove, the present embodiments use one or more temperature detectors (ordata channels) 22 in combination with a model at processor 30, in orderto provide a temperature compensated output. Thus, these embodiments areconfigured to provide an output which is not dependent upon maintainingthe liquid mixture at a particular temperature as it flows through flowpath 28. Rather, these embodiments compensate for substantially anytemperature of the liquid mixture, provided the temperature remainswithin a range predetermined to avoid dissolution at a low end, andexcessive gasification, boiling, etc., at a high end.

Turning now to FIG. 6, in an alternate exemplary embodiment, ACA 20′instruments 24 and 26 are communicably coupled to one or moretransmitters 34, 36, configured to capture data from the instruments andto transmit the data to a processor 30 such as a process controller orworkstation as shown. In particular embodiments, transmitters 34, 36 maybe single or multivariable transmitters of the type availablecommercially from Invensys Systems, Inc. As also shown, fluid flow path28 of ACA 20′ is communicably coupled at an upstream end 38 to analkylation process 40. Fluid flow path 28 is returned to process 40 at adownstream 42 thereof. The foregoing embodiments may also be providedwith various additional aspects that would generally be known to thoseskilled in the art of fluid process control, such as a blow down inletand outlet such as shown at 44 and 46, to facilitate cleaning of flowpath 28, and a pressure sensor(s) 48 to monitor operating pressures.Also, as mentioned above, separator 32 includes a return 50 configuredto return the IB/ps back to process 40, as shown.

Turning now to FIG. 7, in yet another embodiment, an ACA 20″ includes afluid flow path 28′ that includes parallel legs 60 and 62 that divergefrom an upstream end of the flow path 28′, and then reconverge at adownstream end of flow path 28′. The legs 60 and 62 each respectivelyinclude a bypass block valve 64 and 66. In this embodiment, the bypassblock valves 64 and 66 are configured to periodically open and close inopposite synchronization with one another. This configuration thusperiodically stops and starts the flow of the liquid mixture througheach leg 60, 62, while the aggregated liquid mixture (i.e., upstream anddownstream of the legs) flows substantially continuously.

As also shown, this embodiment enables the use of an instrument 24′,having an integral separator that removes hydrocarbon (e.g., IB/ps)present in a gas or liquid phase distinct from that of the liquidmixture (acid catalyst) sample. This integral separator may thus takeadvantage of the alternating start/stop fluid flow through leg 60, toeffectively provide a self-separation of IB/ps from the acid catalystsample while flow through leg 60 is stopped. In this regard, the bypassblock valve 64 can be configured to stop the fluid flow through leg 60for long enough to permit the IB/ps to separate from the acid catalystsample and accumulate within cavity 68 of instrument 24′. The instrument24′ may then capture data from the acid catalyst 70 (e.g., whichcollects at a lower portion of cavity 68), before valve 64 opens tore-start fluid flow. The data provided by instrument 24′ may be combinedwith temperature data from RTD 22 and a model at processor 30 (FIG. 5)as discussed above with respect to ACA 20, to generate concentrationvalues for at least one of the constituents of the alkylation process.

In a particular non-limiting example, instrument 24′ may include a watercut meter, such as the EASZ-1 loop powered water cut meter (EESiFlo®North America, Mechanicsburg, Pa. USA), which has been modified inaccordance with the teachings of the present invention to include anintegral separator in the form of a cavity 68 sized and shaped to enablequantitative accumulation of the aforementioned IB/ps. This ACA 20″ thusprovides for convenient removal of IB/ps that may otherwise interferewith property measurement of the liquid mixture using a singleinstrument 24′, while providing for a temperature compensateddetermination of a concentration of at least one of the constituents ofthe acid catalyst.

In a variation of the foregoing embodiment, one or more optionalinstruments 26′, 26″ may also be used along fluid flow path 28′. Forexample, an optional instrument 26′ may be located in series withinstrument 24′, e.g., within leg 60, or alternatively may be disposed inparallel with instrument 24′, e.g., as shown at 26″ in phantom on leg62. As a non-limiting example, instrument 26′ may include a Foxboro871FT toroidal conductivity sensor, while instrument 26″ may include adensity meter such as the Sarasota™ density meter (Thermo FisherScientific, Inc., Sugar Land, Tex.). It should be recognized, however,that substantially any instrument capable of measuring a property of oneor more of the constituents of the liquid mixture as discussedhereinabove, may be used while remaining within the scope of the presentinvention. It should also be recognized that although embodiments havebeen shown and described herein as having one or two instruments inaddition to a temperature detector, substantially any number (N) ofinstruments may be provided without departing from the scope of thepresent invention.

Note that the embodiment of FIG. 6 is similar to that of FIG. 5, whilehaving some additional aspects that may be desirable in someapplications, such as to facilitate maintenance thereof. For example,isobutane or hot alkylate may be used to flush HF from the sample flowpath, followed by nitrogen blow down to drain for a final purge, in amanner that will be familiar to those skilled in the art, in view of theinstant disclosure.

Optional aspects applicable to substantially any of the embodimentsdiscussed herein may also include, but are not limited to, thefollowing:

-   -   Sample shut-off valves to isolate the analyzer system from the        sample fast loop;    -   Inlets (and outlets) for (IC₄) and nitrogen to purge the system        for maintenance following closure of the shut-off valves;    -   Appropriate metallurgy used throughout (e.g., Hastelloy may be        preferred in particular applications, although “Carpenter 20”        alloy may be used for SA service, and low-carbon steel and/or        Monel may be employed for some components used in HF service);    -   A layout such that sample flows from bottom to top so as to        displace sample in the direction that IB/ps tends to migrate        while purging to drain with nitrogen is done from top to bottom        in a fashion consistent with liquid flow under gravity;    -   The system layout should eliminate “low spots” and “hiding        places” where acid can persist during/after purging;    -   A continuous-flow separator 32 to remove IB/ps from the sample        stream, without which inhomogeneous sample flowing through        sensors could cause erratic responses, as discussed above;    -   Optional sample shutoff (SSO) valves (also referred to as Bypass        Block Valves) 64, 66 (FIG. 7) to automatically stop sample flow        at a fixed interval, e.g., as programmed into the ACA controller        30 (employed as an alternative strategy for eliminating erratic        sensor responses caused by IB/ps) to allow IB/ps to float upward        and away from the sensor(s), yielding a single-phase sample);    -   An optional enclosure, such as shown schematically at 52 of        FIGS. 5, 6, to protect ACA components from the elements, e.g.,        with air purge and an HF gas sensor on the outlet (when        measuring HF catalyst);    -   An optional enclosure and/or heater for use when ambient        temperatures may undesirably cool the liquid mixture as        discussed hereinabove;    -   A flow controller, perhaps as simple as an orifice;    -   A pressure sensor 48 (FIGS. 6, 7); and    -   A temperature sensor (or data channel) 22 in the form of a        stand-alone device, one that is integrated into any one or more        of the instruments 24, 26, etc., or in the form of a data        channel of a multi-channel device, used to explicitly or        implicitly generate temperature information for the liquid        mixture.

The following is a non-limiting list of exemplary sensors and propertiesmeasured, which may be used in particular embodiments of the presentinvention:

-   a. Foxboro 871FT (Invensys®) conductivity meter;-   b. Foxboro CFS10 (Invensys®) Coriolis flow meter (density and    temperature; flow is also monitored to provide information about    analyzer operation but is not used in the calculation of acid    composition);-   c. Agar Corporation OW-301 water cut meter (microwave);-   d. Eesiflo International EASZ1 water monitor (dielectric);-   e. K-Patents PR-01-S process refractometer; and-   f. Low-field NMR, i.e., proton resonance frequency <50 MHz.

As discussed herein, instruments 24, 24′, 26, 26′, etc., (andtemperature detector 22) have been described in various embodiments assingle channel, stand-alone devices. However, it should be recognizedthat these various instruments and temperature detector may includedevices of substantially any type, including multi-channel devices,provided they have one or more data channels which are responsive toconcentrations of any one or more constituents of the liquid mixture(e.g., of the acid (HF or SA), the acid-water fraction, and/or ASO) asdescribed herein. For example, multi-channel devices such as theabove-referenced NIR, FTNIR (Fourier Transform NIR), NMR, and/or Ramanspectrometers, may be used as one or more of the devices 22, 24, 24′,26, 26′, etc.

For example, with reference back to FIG. 5, in particular embodiments,temperature detector 22 and instrument 24 may take the form of a singlemulti-channel (e.g., NIR) spectrometer. A gas/liquid separator 32 may bedisposed in series with the NIR spectrometer to enable substantiallycontinuous sample flow through flow channel 28 as discussed above.(Similarly, with reference to FIG. 7, temperature detector 22,instrument 24′, and/or instrument 26′ may take the form of a singlemulti-channel spectrometer modified to include an integral separator ina parallel flow path arrangement as also shown and describedhereinabove.) One channel of the spectrometer may thus be configured toserve as detector 22 to generate temperature information for the liquidmixture, while another channel may serve as instrument 24, 24′, etc., togenerate information corresponding to concentration of one of thecomponents of the liquid mixture as discussed hereinabove. In avariation of this approach, a third channel of the NIR spectrometer maybe used to generate information as described hereinabove with respect toinstrument 26, 26′, etc.

Moreover, rather than generating temperature information directly,channel 22 of the spectrometer may be used to generate datacorresponding to another aspect of the liquid mixture, so that multiple(e.g., three or more) channels of the spectrometer may be used to gathersufficient information to effectively infer the temperature of theliquid mixture, as described in greater detail hereinbelow. In thismanner, the need for directly determining the temperature of the liquidmixture is obviated, e.g., so that channel 22 may be used to gatherother useful information. Thus to summarize this example, three channelsof the spectrometer correspond to devices 22, 24, and 26, with channel22 used either for direct (explicit), or indirect (inferential)temperature measurement using the model, as discussed in greater detailhereinbelow.

Improvements Over Standard Implementations of NIR and NMR

At least three features of the embodiments discussed herein, orpractices associated with their implementation, represent significantimprovements over established approaches to acid catalyst analysis basedon conventional NMR and NIR spectroscopy. First, in particularembodiments, separator 32 (FIGS. 5, 6), removes IB/ps, which permitssubstantially real-time analysis of continuously flowing sample asdiscussed hereinabove. In alternate embodiments, such as shown anddescribed hereinabove with respect to FIG. 7, a separator may beincorporated within an instrument such as at 24′, which, in combinationwith use of a flow path having parallel legs 60, 62, also enables thecontinuous flow of liquid mixture (e.g., acid catalyst sample). Thiscontrasts with conventional NMR and NIR approaches, which generallyrequire a stationary sample, i.e., periodic, frequent stop-flow toensure that any IB/ps floats up and clears the sample probe ortransmission cell, respectively, where analysis takes place. Thisincorporation of a separator into the sample flow path thus provides forsubstantially real-time and continuous sample analysis.

Second, property predictions by the embodiments of the ACA discussedherein are substantially insensitive to variation in sample temperaturebecause responses from a plurality of channels are used to make propertymodels in which temperature is an implicit or explicit variable. Modelsincorporating responses of instruments 22, 24, 24′, 26, 26′, etc., whosepurpose is to follow changes in composition, e.g., the CFS10 (totalhydrocarbon) and the 871FT (water), may be used to compensate fortemperature implicitly or explicitly, obviating the requirement forsampling systems that ensure presentation of an isothermal sample foranalysis.

The apparent simplicity of NIR and NMR spectra belies the complexity ofsuch sample conditioning systems, which may cost up to twice as much asthe base spectrometer. The current state of the art in process NMRdepends on an isothermal sample. Though not the case with NIRspectroscopy generally, the established approach to NIR analysis of acidcatalyst is decidedly isothermal because the property models areisothermal, and samples' spectral responses vary significantly as afunction of temperature. Embodiments of the present invention may thusutilize an NIR spectrometer without the need for an isothermal sample,such as by use of NIR models developed as described herein, tocompensate for sample temperature implicitly (e.g., inferentially) orexplicitly. Embodiments including such a model, in combination with aseparator to remove phase-separated isobutane, may dramatically reducethe cost to install and maintain an NIR analyzer system relative to theprior art.

Third, instruments 24, 24′, 26, 26′, etc., (and detectors 22) used invarious embodiments of the ACA have core technology that is relativelysimple, robust, simple to install, and easy to commission. Installationand commissioning of conventional NIR and NMR systems, including theirtemperature conditioning approaches, can take weeks. By contrast, theACA 20, 20′, 20″, etc., has relatively simple installation requirements,while commissioning may typically be completed within two days. Perhapseven more significant, the combined mean-time-before-failure ofrepresentative instruments 24 and 26, such as the Invensys® CFS10Coriolis flowmeter and the Invensys® 871FT conductivity sensor isexpected to be relatively long, e.g., estimated by one independententity to be more than 29 years.

Calibration: Modeling Concentration in Terms of Instrument Responses

As discussed hereinabove in a previous section (Analytical Problem),aspects of the present invention include a two-step process forobtaining concentration values for components in acid catalyst based oninstrument responses R₁ and R₂. In general terms, a property P ispredicted by applying MODEL _(P) to responses measured on that sample:P=MODEL _(P) ·[R ₁ ,R ₂ ,R ₃ , . . . ,R _(N)]  (5)where the responses R₁, R₂, R₃, . . . , R_(N) may be measured on Ndifferent single-channel instruments, or on a single N-channelspectrometer. FIG. 8 shows the process in terms of data collected asdepicted in Table 2 for the three-channel case, and then analyzed tocreate a model, which is then applied to the responses R₁, R₂, R₃, . . ., R_(N) measured by the instruments for a sample of unknown composition.

TABLE 2 Example of a calibration data set for a 3-channel analyzersystem SAMPLE INFORMATION CHANNEL RESPONSES PROPERTY VALUES (LAB ORONLINE) Lab ID Date/Time Ch. 1 Ch. 2 Ch. 3 % Acid % Hydrocarbon % Water1 Day 1 R₁₁ R₂₁ R₃₁ A₁ H₁ W₁ 2 Day 2 R₁₂ R₂₂ R₃₂ A₂ H₂ W₂ 3 Day 3 R₁₃R₂₃ R₃₃ A₃ H₃ W₃ . . . . . . . . . . . . . . . . . . . . . . . . n Day nR_(1n) R_(2n) R_(3n) A_(n) H_(n) W_(n)

As used herein, the term “modeling” refers to the process ofmathematically relating responses obtained from a plurality of responsechannels to the known chemical composition of calibration samples, theresult being a “model.” As used herein, the term “model” is not limitedin form to a system of linear equations such as depicted in Equations(4) or (5), nor is it limited to use of responses R₁, R₂ from only twoinstruments. Rather, “model” refers to any equation or a system ofequations, which may include multiple terms for variables (parameters)measured by the embodiments shown and described herein, and which aloneor in combination predict one or more of the component properties(concentrations) of interest.

Calibration: Explicit and Implicit Temperature Compensation

Furthermore, models may be developed so as to be capable of accuratelypredicting properties even when variation in sample temperature has adirect effect on one or more inputs R_(i) apart from e.g., a componentconcentration change. Referring to Equations (1), (2), and (3), thiswould mean that one or more values d(a_(i))/dT, d(h_(i))/dT, andd(w_(i))/dT are nonzero. In one approach, predictions can be madeinsensitive to temperature by employing responses R_(i) from three ormore single-channel instruments, or from an N-channel spectrometer(N≧3). If Equation (4) is understood to apply under isothermalconditions (dT=0), then Equation (6) illustrates the addition of a thirddevice to deal implicitly with the additional degree of freedomresulting from temperature variation (the boundary condition A+H+W=100still applies):R ₁ =a ₁ ·A+h ₁ ·H+w ₁ ·WR ₂ =a ₂ ·A+h ₂ ·H+w ₂ ·WR ₃ =a ₃ ·A+h ₃ ·H+w ₃ ·W  (6)

Provided that R₁, R₂, and R₃ relate substantially uniquely to T, andadequate variation exists among all coefficients a_(i), h_(i), or w_(i), a suitable multivariable modeling method such as PLS, can be usedto obtain models that provide predictions for A, H, and W as depicted inEquation (5), which are substantially insensitive to temperaturevariation. This can be termed passive or implicit temperaturecompensation.

In explicit or active temperature compensation, models are developedwhich incorporate temperature as a measured variable. Equation (7) is analternative way to express the relationship between the concentrationsof interest and measured responses, with temperature (T) being anexplicit variable (the boundary condition applying still):A=a′ ₁ ·R ₁ +a′ ₂ ·R ₂ +t _(A) ·TH=h′ ₁ ·R ₁ +h′ ₂ ·R ₂ +t _(H) ·T

W=w′ ₁ ·R ₁ +w′ ₂ ·R ₂ +t _(w) ·T

where T, t_(A), t_(H), and t_(w) have been substituted for R₃, a′₃, h′₃,and w′₃, respectively. Thus, whether models incorporate temperatureimplicitly or explicitly, the development of N property models for adetermined system where A+H+W=100 requires a minimum of N measuredparameters.Calibration: Characteristics of the Data Set

At least three observations about samples and property values should benoted concerning the calibration sample set and the calibration process.

-   -   Concentration Ranges. In particular embodiments, the sample set        should include samples whose composition spans the full range of        relevant property values that the process will exhibit and the        analyzer will be required to analyze.    -   Sample Composition. To the extent practical, the sample set in        particular embodiments should also have all possible        combinations of component concentrations.    -   Temperature Range. When the goal is to develop models that        provide substantially accurate predictions when temperature        varies, calibration samples should generally span the full range        of temperatures of interest manner that is not correlated with        composition.    -   Data Modeling. Calibration involves the statistical reduction of        data for a population of samples. Accordingly, multivariable        statistical modeling methods such as MLR (multiple linear        regression) or PLS (partial least squares), and/or other        modeling methods known to those skilled in the art may be used.

Additional Considerations Related to Representative Implementation

The following are practices related to the implementation of variousembodiments of the ACA.

Calibration of Sensors

The above-referenced 871FT conductivity, the CFS10 Coriolis flowmeter,or any other sensor used in the ACA embodiments hereof will not berequired to report percent acid, percent water, or percent organic(e.g., ASO) directly. Instead, the “raw” responses from the instrumentwill be used both for the creation of property models and for routinecomposition prediction using those models. Thus, signals from theinstruments are gathered into a common data handling device (e.g.,processor 30) where models are applied to predict percent (%) acid,percent (%) hydrocarbon, and percent (%) water.

Generation of Reference Values for Modeling

The property (lab) values noted may come from a variety of sources. Atraditional analysis approach may be used, which includes obtainingsamples and testing them in the laboratory by a conventional (e.g.,manual) test method. Alternatively, for development purposes, it may bepossible to use data captured from current installations that employspectrometric analyzers. These data may be used to calibrate embodimentsof the present invention.

Temperature as an Analytical Variable

As mentioned hereinabove, conventional process spectrometer systemsemployed for the analysis of acid catalyst, i.e., NIR(HF) and NMR(SA)commonly are designed to control sample temperature. It has beengenerally understood that such control was required in order ensurereproducibility of samples' spectral response, which are known generallyto exhibit variation as a function of temperature. Similarly, as alsomentioned above, the various devices incorporated into embodiments ofthe present invention may also have some temperature dependency. Assuch, it should be recognized that the embodiments hereof may alsoinclude such conventional sample temperature control.

However, as also discussed above, particular embodiments of the presentinvention avoid the need for such temperature control by providing fortemperature compensation. This temperature compensation may be providedby capturing the temperature either explicitly or implicitly. Forexample, temperature may be captured explicitly using temperaturedetector 22 (FIGS. 5-7), and/or by using temperaturecapture/compensation technology commonly incorporated into variousinstruments 24, 26, etc. (In this regard, for example, in addition toflow and density, the above-referenced CFS10 Coriolis flowmeter alsoreports sample temperature.) Embodiments of the present invention maythus include temperature as a measured variable (e.g., a data channel)via stand-alone temperature detector 22. This temperature informationmay then be used with the aforementioned data model, to compensate fortemperature-dependent changes in responses/data provided by the otherinstruments (e.g., the other data channels).

Alternatively, as also discussed above, sample temperature may becaptured implicitly, such as by providing a sufficient number ofsubstantially mutually distinct data channels (e.g., three or more forthe acid catalysts described hereinabove) provided by variousinstruments used in combination, and/or by the use of multi-channeldevices such as the aforementioned spectrometers.

Regardless of which of these approaches are used, the variousembodiments of the present invention may use this direct or inferredtemperature information to compensate for the particular temperature ofthe liquid mixture, to reduce or substantially eliminate the requirementfor sample conditioning (i.e., isothermal temperature control) such ascommonly used with spectrometric analyzers.

Validation

After modeling, the accuracy of predictions made by the ACA 20, 20′,20″, etc., with the model may be validated through the process depictedin FIG. 9.

The standard deviation on the difference between Lab and Predictedvalues, Stdev(D), is sometimes referred to as SEP (Standard Error ofPrediction) or RMSEP (root mean square error of prediction). SEP issimply a measure of agreement between the Lab and Predicted values.Insofar as both the predicted values and the Lab values have associateduncertainties, the name SEP implies inappropriately that the differencesare due to errors in the predicted values only, whereas reference valuesinvariably have associated errors and therefore may be referred tosimply as SE (standard error).

G. Additional Considerations ReVAP and Alkad Additive Systems (HFAlkylation)

The analytical problem may become more complex if yet another component,e.g., an additive such as per the ReVAP™ or Alkad™ processes (UOP, LLC,Des Plaines, Ill.) is added into the catalyst, such as to reduce HFvolatility. In these and other applications involving additionalcomponents or additives, embodiments of the invention as discussedherein may be used substantially as described, or with variousmodifications made to facilitate their use. For example, an ACA system20 and/or 20′ (FIGS. 5, 6) may be provided with two instruments 24, 26.Instrument 24 may include a conductivity sensor such as theaforementioned Foxboro 871FT conductivity sensor. Instrument 26 mayinclude a Raman spectrometer, e.g., connected via fiber optics to thesample flow path 28. The Raman spectrometer 26 may be used inconjunction with a gas/liquid separator 32, or with a bifurcated sampleflow path and bypass block valve 66 (FIG. 7) to enable substantiallycontinuous sample flow as discussed hereinabove. A temperature detector22 may be included as a discrete component (as shown), or providedinferentially by the Raman spectrometer as discussed hereinabove.Alternatively, a discrete temperature detector may be integrated intoany one of various instruments 24, 26, etc. In this regard, as anoptional variation of this approach, another instrument 26 may be used,such as a flowmeter (e.g., the Foxboro CFS 10 Coriolis flowmeterdiscussed hereinabove), which includes an integral temperature detector.As further options, one or more pressure sensors 48 may be provided,such as shown and described with respect to FIG. 6.

In these exemplary configurations, the conductivity sensor 24 and theRaman spectrometer 26 may be used as described herein to convenientlyanalyze a conventional HF catalyst which may include: HF (roughly82%-95%); Acid Soluble Oil (ASO) (5%-15%); and water (0.5%-2%). HF andASO may thus be measured by the Raman spectrometer (using themodel/processor 30); and water may be measured using the conductivitysensor. Process temperature measured by detector 22 would enable themeasurements of HF and ASO to be conveniently compensated fortemperature.

These embodiments may also be used to analyze more complex systems inwhich one or more additional components (such as with ReVAP or Alkadprocesses) are added to the fluid mixture. For example, a conventionalReVAP HF catalyst system includes HF, ASO, water, and an additive (e.g.,sulfolane). So while the conductivity sensor 24 may be used to measurewater, the remaining components (HF, ASO, and the sulfolane additive)may be measured using the Raman spectrometer 26 in combination with themodel/processor 30. Thus, in both cases, i.e., those with and withoutadditional components, the water may be measured by use of theconductivity sensor 24, while the Raman spectrometer may be used tomeasure the balance of the components in the acid catalyst mixture. Inother words, in each case, the conductivity sensor provides a responsethat can be correlated with water concentration. And in each case, theRaman spectrum contains distinct responses that correlate directly withthe other components in the sample: HF and ASO; and in the case of theReVAP and Alkad processes, the additive.

It is noted that the Raman spectrum has distinct responses for allcomponents of these processes except water. Water has essentially noRaman signal and is thus measured by conductivity as discussed above.Thus, rather than depending on a conventional statistical modelingmethodology, this Raman-based analyzer system may be calibrated withrelatively few samples. Moreover, it is noted that these embodiments donot rely on conventional active temperature control to carefullymaintain the process fluid at predetermined temperatures duringanalysis. Rather, the model 30 used by embodiments of the presentinvention as described hereinabove effectively compensates fortemperature variations when calculating concentrations. In this regard,while the conductivity measurement varies in accordance withtemperature, this measurement is substantially independent of theconcentrations of the other components of the sample. This aspect, incombination with the Raman spectrometer's relative insensitivity totemperature variation, tends to facilitate this temperature compensationapproach, to thus obviate the need for the conventional temperaturecontrol associated with the aforementioned NIR, FTNIR, and NMRapproaches.

It should be recognized that conventional temperature controlled NIR,FTNIR, etc., may be used to measure components in an HF alkylationcatalyst having additives associated with the ReVAP and Alkadapproaches. However, those skilled in the art will recognize thatconventional approaches for developing NIR property models for thesecatalyst-plus-additive samples may be sufficiently cumbersome and/orinaccurate as to make NIR impractical for such applications. In thisregard, conventional laboratory analysis of catalyst composition may beinsufficiently accurate to sustain the statistically-based PLS modelingmethodology described above. Moreover, although models may be availablefor some additive-containing samples, a new model would generally needto be developed when a new additive is used. So while conventional modeldevelopment approaches may be used to enable use of NIR, FTNIR, etc.,for samples having additives, these approaches may be relativelyimpractical.

Alternative Applications

Embodiments of the present invention have been shown and describedherein as particularly useful in alkylation processes, e.g., due to thebenefits of higher accuracy relative to solitary instruments, and lowerprice and ease of use vs general purpose spectrometric analyzers.However, it should be recognized that these embodiments more broadlyprovide a multi-channel multi-variable analyzer, e.g., by theintegration of two or more disparate instruments into a system, and/orby the use of temperature compensation rather than temperatureconditioning, that provides many of the benefits of a multi-channelspectrometer in a generally simpler, more robust, and cost effectivemanner, which may lend itself to creation and application of modelsusing techniques similar to those applied in quantitative spectrometry.

An example of another application that may benefit from embodiments ofthe present invention may include one that is related to operation of HFalkylation units. This application concerns control of an HFregeneration tower (a distillation unit that pushes high-purity HFoverhead and leaves water and polymer/ASO at the bottom in the form of aresidue for disposal). The objective of this distillation unit is toremove as much HF out of the residue as possible to minimize the needfor caustic materials to neutralize any remaining HF in the residueprior to disposal (e.g., incineration).

The residue may thus be pumped through the embodiments of, for example,FIGS. 5 and 6, to measure percent (%) organic, percent (%) HF, andpercent (%) water. In this manner, operation of the distillation unitmay be continued until the percent (%) HF reaches a sufficiently lowlevel.

Having described various embodiments of the present invention, exemplarymethods of operation will now be described in connection with thefollowing Tables 3 and 4.

Referring to Table 3, an exemplary method is provided for on-lineconcentration determination of components in a liquid hydrocarbonmixture flowing through an alkylation process, which includeshydrocarbons and water. The method includes supplying 100 the liquidmixture to an instrument configured to have responsivities toconcentrations of one of the acid, ASO, and water, independently of theconcentrations of the others of the acid catalyst, ASO, and water. Theliquid mixture is supplied 102 to a temperature detector, and supplied103 to a second instrument. A property of the liquid mixture is measuredwith the first instrument at 104 and with the second instrument at 105,and temperature data is generated at 106. Property and temperature datais captured at 108, and a processor uses the data and a model ofresponsivities to various concentrations of the acid, ASO, and water atvarious temperatures, to determine 110 a temperature compensatedconcentration of at least one of said acid, ASO and water, in the liquidmixture.

TABLE 3 100 supplying the liquid mixture to an instrument; 102 supplyingthe liquid mixture to a temperature detector; 103 supplying the liquidmixture to a second instrument 104 measuring a property of the liquidmixture using the instrument; 105 measuring a property of the liquidmixture using the second instrument 106 generating temperature data forthe liquid mixture using the temperature detector; 108 capturing, with aprocessor, data generated by the instrument and temperature detector;110 determining, with the processor, using the data in combination witha model, a temperature compensated concentration of at least one of theacid, ASO, and water.

Optional aspects of the foregoing method are described in connectionwith Table 4. As shown, the temperature compensated concentration isfiltered at 112. A Raman spectrometer is optionally used as theinstrument at 114. At 116, the liquid mixture is optionally supplied toan other instrument, in which the instruments are configured to havemutually distinct responsivities to concentrations of the acid, ASO, andwater, and both instruments are used by the processor to determinetemperature compensated concentration of at least two constituents ofthe liquid mixture. A conductivity measurement device is optionally usedas the other instrument at 118. Hydrocarbons separated from the bulkacid catalyst as a distinct phase (liquid or gas) are optionally removed120 from liquid sample mixture prior to using the instrument forproperty analysis, optionally while the liquid mixture is conveyedsubstantially continuously in a downstream direction. Optionally, at121, the instruments and temperature detector are configured as amulti-channel Raman spectrometer, having at least three channels, e.g.,for generating information corresponding to three mutually distinctparameters of the liquid mixture, for explicit or inferentialtemperature detection of the liquid mixture. The separating is effectedusing an alternating stop flow via parallel flow paths at 122. Theliquid mixture is obtained from an acid catalyst stream in a hydrocarbonconversion process, including either HF or SA at 124. A model is used at126 which includes a model data set of expected outputs from theinstruments under a plurality of known concentrations of acid, ASO,water, and optionally, an additive.

TABLE 4 112 temperature compensated concentration is filtered 114Instrument is a Raman spectrometer 116 liquid mixture is optionallysupplied to an other instrument 118 Other instrument is a conductivitymeasurement device 120 Phase-separated hydrocarbons optionally separatedfrom liquid mixture prior to using the instrument(s), optionally whilethe liquid mixture is conveyed substantially continuously downstream 121Optionally, the instruments and temperature detector are configured inthe form of a multi-channel Raman spectrometer, having at least threechannels, e.g., configured for generating information corresponding tothree mutually distinct parameters of the liquid mixture, for explicitor inferential temperature detection of the liquid mixture. 122separating effected using alternating stop flow via parallel flow paths124 liquid mixture obtained from an HF or SA acid catalyst stream in ahydrocarbon conversion process 126 Model used includes model data set ofexpected outputs from the instruments under a plurality of knownconcentrations of acid, ASO, water, and optionally, an additive.

It should be recognized that in the foregoing embodiments, instruments24, 24′ 26, and 26′, etc., may be incorporated into a single device,provided they have mutually distinct responsivities to concentrations ofthe acid catalyst, ASO, and water. So for example, these instruments mayinclude a single NMR or NIR spectrometer capable of detecting multipleresponses to one or more stimuli, and whose sampling system isconfigured with a sensor to measure the sample temperature, which may beused to compensate for temperature variation in the case where thesampling system is not designed to control sample temperature.Alternatively, the sampling system does not actively control sampletemperature, but instead a calibration data set such as that describedin Table 2 is acquired across a wide range of temperatures T_(n) suchthat the effect of temperature on responses R₁, R₂, R₃, . . . , R_(n) isrepresented in the calibration data set across a range of relevanttemperatures to permit acid, ASO, and water to be modeled without directapplication of a correction for measured temperature.

It should also be recognized that although the various embodimentshereof have been shown and described as suitable for online use, e.g.,by direct connection to an alkylation process, these embodiments mayalso be used in an offline mode without departing from the scope of thepresent invention.

It should be noted that the various modules and other components of theembodiments discussed hereinabove, including processor 30, may beconfigured as hardware, as computer readable code stored in any suitablecomputer usable medium, such as ROM, RAM, flash memory, phase-changememory, magnetic disks, etc., and/or as combinations thereof, withoutdeparting from the scope of the present invention.

It should be understood that any of the features described with respectto one of the embodiments described herein may be similarly applied toany of the other embodiments described herein without departing from thescope of the present invention.

In the preceding specification, the invention has been described withreference to specific exemplary embodiments for the purposes ofillustration and description. It is not intended to be exhaustive or tolimit the invention to the precise form disclosed. Many modificationsand variations are possible in light of this disclosure. It is intendedthat the scope of the invention be limited not by this detaileddescription, but rather by the claims appended hereto.

The above systems are implemented in various computing environments. Forexample, the present invention may be implemented on a conventional IBMPC or equivalent, multi-nodal system (e.g., LAN) or networking system(e.g., Internet, WWW, wireless web), and/or conventional process controlnetwork. All programming and data related thereto are stored in computermemory, static or dynamic or non-volatile, and may be retrieved by theuser in any of: conventional computer storage, display (e.g., CRT, flatpanel LCD, plasma, etc.) and/or hardcopy (i.e., printed) formats. Theprogramming of the present invention may be implemented by one skilledin the art of computer systems and/or software design.

Having thus described the invention:

1. An apparatus for on-line concentration determination of components ina liquid hydrocarbon mixture flowing through an alkylation process,which liquid hydrocarbon mixture includes an unknown concentration ofcomponents including hydrocarbons and water, said apparatus comprising:a fluid flow path configured to convey the liquid mixture continuouslyin a downstream direction from the alkylation process; a firstinstrument disposed along the fluid flow path, and configured formeasuring a property of the liquid mixture, the first instrumentconfigured to have responsivities to concentrations of one of thecomponents, substantially independent of the concentrations of thewater; a temperature detector configured to generate temperature datafor the liquid mixture; a second instrument disposed along the fluidflow path, and configured for measuring another property of the liquidmixture; the first and second instruments configured to have mutuallydistinct responsivities to concentrations of the components; a model ofresponsivities to various concentrations of the components at varioustemperatures; a filter module communicably coupled to said processor,said filter configured to filter said temperature compensatedconcentration; and a processor configured to capture data generated bythe temperature detector and the first and second instruments, and touse the data in combination with said model to determine a temperaturecompensated concentration of said components in said liquid mixturewhile the liquid mixture flows continuously through the fluid flow path.2. The apparatus of claim 1, wherein the liquid hydrocarbon mixturecomprises an acid catalyst for hydrocarbon conversion including unknownconcentrations of an acid, an acid-soluble-oil (ASO), and water.
 3. Theapparatus of claim 2, wherein the liquid hydrocarbon mixture furthercomprises one or more additive.
 4. The apparatus of claim 3, wherein theadditive comprises sulfolane.
 5. The apparatus of claim 1, wherein atleast one of said instruments comprises a conductivity measurementdevice.
 6. The apparatus of claim 3, wherein said fluid flow path isconfigured to convey the liquid mixture in a downstream direction froman acid catalyst stream in a hydrocarbon conversion process to theinstrument.
 7. The apparatus of claim 6, wherein the instruments areconfigured to have mutually distinct responsivities to concentrations ofthe acid, the ASO, the water, and the additive; and wherein theprocessor is configured to capture data generated by the temperaturedetector and the instruments and to use the data in combination with themodel to generate a temperature compensated concentration of the acidcatalyst, the ASO, the water, and the additive, in said liquid mixture.8. The apparatus of claim 1, wherein said first instrument comprises aRaman spectrometer, and said second instrument comprises a conductivitysensor.
 9. The apparatus of claim 8, comprising a third instrumentdisposed along said fluid flow path.
 10. The apparatus of claim 9,wherein said third instrument comprises a flowmeter.
 11. The apparatusof claim 9, wherein said third instrument comprises a densitymeasurement device.
 12. The apparatus of claim 8, wherein said fluidflow path comprises a separator disposed upstream of the firstinstrument, the separator configured to remove hydrocarbon present in agas or liquid phase distinct from that of the liquid mixture, whereinthe fluid flow path is configured to convey the liquid mixturecontinuously to the first instrument.
 13. The apparatus of claim 12,wherein said Raman spectrometer comprises multiple channels.
 14. Theapparatus of claim 13, wherein the multiple channels are configured forgenerating information corresponding to mutually distinct parameters ofthe liquid mixture.
 15. The apparatus of claim 14, wherein thetemperature of the liquid mixture is determined inferentially.
 16. Theapparatus of claim 12, wherein the separator is disposed upstream ofboth of said first instrument and said second instrument within saidfluid flow path.
 17. The apparatus of claim 1, wherein the fluid flowpath comprises parallel legs and the continuously flowing liquid mixturealternates between said legs.
 18. The apparatus of claim 1, comprisingone or more other instruments configured for measuring one or more otherproperties of the liquid mixture.
 19. The apparatus of claim 18, whereinthe one or more other instruments are selected from the group consistingof: pH probes; ion-selective electrodes; viscometers; refractive indexprobes; beta gauges; densitometers; conductivity meters; photometers;flow meters; water cut measurement instruments; temperature probes(RTDs, TCs, thermisters, PRTs); NIR detectors; FTNIR detectors;filter-based NIR photometers; UV (ultra-violet) detectors; Ramanspectrometers; NMR spectrometers; water-cut meters; and combinationsthereof.
 20. The apparatus of claim 1, wherein the temperature detectoris disposed on at least one of the instruments.
 21. The apparatus ofclaim 1, wherein said model comprises a model data set of expectedoutputs from the first and second instruments when measuring liquidsamples having a plurality of known concentrations of acid,acid-soluble-oil (ASO), and water.
 22. The apparatus of claim 21,wherein said model comprises a model data set of expected outputs fromthe first and second instruments when measuring liquid samples having aplurality of known concentrations of acid, acid-soluble-oil (ASO),water, and an additive.
 23. The apparatus of claim 2, wherein the acidin said acid catalyst is hydrofluoric acid (HF) acid.
 24. The apparatusof claim 2, wherein the acid in said acid catalyst is sulfuric acid(SA).